Application of L-EDA in metabonomics data handling: global metabolite profiling and potential biomarker discovery of epithelial ovarian cancer prognosis
Application of L-EDA in metabonomics data handling: global metabolite profiling and potential biomarker discovery of epithelial ovarian cancer prognosis
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L-EDA 在代谢组学数据处理中的应用：整体代谢物分析和上皮性卵巢癌预后的潜在生物标志物发现
DOI：
10.1007/s11306-011-0286-3
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发表时间：
2011-12-01
期刊：
影响因子：
3.6
通讯作者：
Lin, Xiaohui
中科院分区：
文献类型：
--
作者：
Chen, Jing;Zhang, Yang;Lin, Xiaohui
提出了解决方案容量有限估计分布算法（L-EDA），并将其应用于卵巢癌预后生物标志物的发现，以阐述其在代谢组学研究中的潜力。采用液相色谱-质谱法对健康女性、上皮性卵巢癌 (EOC)、复发性 EOC 和非复发性 EOC 患者的血清进行分析。 L-EDA 处理代谢数据以发现潜在的 EOC 预后生物标志物。经过 L-EDA 过滤后，从 714 个变量中选择了 78 个，通过主成分分析可视化四组之间的关系，观察到通过 L-EDA 过滤的变量，可以区分非复发性 EOC 和复发性 EOC 组，而这在初始数据中是不可能的。 Wilcoxon 检验中 P < 0.05 的 5 个代谢物（6 个变量）被认为是潜在的 EOC 预后生物标志物，其对复发性 EOC 和非复发性 EOC 的分类准确率为 86.9%，对健康 + 非复发性 EOC 和 EOC + 复发性 EOC 的分类准确率为 88.7%。结果表明，L-EDA 是代谢组学研究中潜在生物标志物发现的有力工具。
Solution capacity limited estimation of distribution algorithm (L-EDA) is proposed and applied to ovarian cancer prognosis biomarker discovery to expatiate on its potential in metabonomics studies. Sera from healthy women, epithelial ovarian cancer (EOC), recurrent EOC and non-recurrent EOC patients were analyzed by liquid chromatography-mass spectrometry. The metabolite data were processed by L-EDA to discover potential EOC prognosis biomarkers. After L-EDA filtration, 78 out of 714 variables were selected, and the relationships among four groups were visualized by principle component analysis, it was observed that with the L-EDA filtered variables, non-recurrent EOC and recurrent EOC groups could be separated, which was not possible with the initial data. Five metabolites (six variables) withP< 0.05 in Wilcoxon test were discovered as potential EOC prognosis biomarkers, and their classification accuracy rates were 86.9% for recurrent EOC and non-recurrent EOC, and 88.7% for healthy + non-recurrent EOC and EOC + recurrent EOC. The results show that L-EDA is a powerful tool for potential biomarker discovery in metabonomics study.